In this paper, actual personal identifiable information (PII) texts are analyzed to capture different types of PII sensitivities. The sensitivity of PII is one of the most important factors in determining an individua...In this paper, actual personal identifiable information (PII) texts are analyzed to capture different types of PII sensitivities. The sensitivity of PII is one of the most important factors in determining an individual’s perception of privacy. A “gradation” of sensitivity of PII can be used in many applications, such as deciding the security level that controls access to data and developing a measure of trust when self-disclosing PII. This paper experiments with a theoretical analysis of PII sensitivity, defines its scope, and puts forward possible methodologies of gradation. A technique is proposed that can be used to develop a classification scheme of personal information depending on types of PII. Some PII expresses relationships among persons, some specifies aspects and features of a person, and some describes relationships with nonhuman objects. Results suggest that decomposing PII into privacy-based portions helps in factoring out non-PII information and focusing on a proprietor’s related information. The results also produce a visual map of the privacy sphere that can be used in approximating the sensitivity of different territories of privacy-related text. Such a map uncovers aspects of the proprietor, the proprietor’s relationship to social and physical entities, and the relationships he or she has with others.展开更多
It is widely common that mobile applications collect non-critical personally identifiable information(PII)from users'devices to the cloud by application service providers(ASPs)in a positive manner to provide preci...It is widely common that mobile applications collect non-critical personally identifiable information(PII)from users'devices to the cloud by application service providers(ASPs)in a positive manner to provide precise and recommending services.Meanwhile,Internet service providers(ISPs)or local network providers also have strong requirements to collect PIIs for finer-grained traffic control and security services.However,it is a challenge to locate PIIs accurately in the massive data of network traffic just like looking a needle in a haystack.In this paper,we address this challenge by presenting an efficient and light-weight approach,namely TPII,which can locate and track PIIs from the HTTP layer rebuilt from raw network traffics.This approach only collects three features from HTTP fields as users'behaviors and then establishes a tree-based decision model to dig PIIs efficiently and accurately.Without any priori knowledge,TPII can identify any types of PIIs from any mobile applications,which has a broad vision of applications.We evaluate the proposed approach on a real dataset collected from a campus network with more than 13k users.The experimental results show that the precision and recall of TPII are 91.72%and 94.51%respectively and a parallel implementation of TPII can achieve 213 million records digging and labelling within one hour,reaching near to support 1Gbps wirespeed inspection in practice.Our approach provides network service providers a practical way to collect PIIs for better services.展开更多
Identity-based threshold signature(IDTS)is a forceful primitive to protect identity and data privacy,in which parties can collaboratively sign a given message as a signer without reconstructing a signing key.Neverthel...Identity-based threshold signature(IDTS)is a forceful primitive to protect identity and data privacy,in which parties can collaboratively sign a given message as a signer without reconstructing a signing key.Nevertheless,most IDTS schemes rely on a trusted key generation center(KGC).Recently,some IDTS schemes can achieve escrow-free security against corrupted KGC,but all of them are vulnerable to denial-of-service attacks in the dishonest majority setting,where cheaters may force the protocol to abort without providing any feedback.In this work,we present a fully decentralized IDTS scheme to resist corrupted KGC and denialof-service attacks.To this end,we design threshold protocols to achieve distributed key generation,private key extraction,and signing generation which can withstand the collusion between KGCs and signers,and then we propose an identification mechanism that can detect the identity of cheaters during key generation,private key extraction and signing generation.Finally,we formally prove that the proposed scheme is threshold unforgeability against chosen message attacks.The experimental results show that the computation time of both key generation and signing generation is<1 s,and private key extraction is about 3 s,which is practical in the distributed environment.展开更多
Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Buildin...Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Building a PII retrieval service over multi-cloud,which is a modern strategy to make services stable where multiple servers are deployed,seems to be a promising solution.However,three major technical challenges remain to be solved.The first is the privacy and access control of PII.In fact,each entry in PII can be shared to different users with different access rights.Hence,flexible and fine-grained access control is needed.Second,a reliable user revocation mechanism is required to ensure that users can be revoked efficiently,even if few cloud servers are compromised or collapse,to avoid data leakage.Third,verifying the correctness of received PII and locating a misbehaved server when wrong data are returned is crucial to guarantee user’s privacy,but challenging to realize.In this paper,we propose Rainbow,a secure and practical PII retrieval scheme to solve the above issues.In particular,we design an important cryptographic tool,called Reliable Outsourced Attribute Based Encryption(ROABE)which provides data privacy,flexible and fine-grained access control,reliable immediate user revocation and verification for multiple servers simultaneously,to support Rainbow.Moreover,we present how to build Rainbow with ROABE and several necessary cloud techniques in real world.To evaluate the performance,we deploy Rainbow on multiple mainstream clouds,namely,AWS,GCP and Microsoft Azure,and experiment in browsers on mobile phones and computers.Both theoretical analysis and experimental results indicate that Rainbow is secure and practical.展开更多
TarGuess-I is a leading model utilizing Personally Identifiable Information for online targeted password guessing.Due to its remarkable guessing performance,the model has drawn considerable attention in password secur...TarGuess-I is a leading model utilizing Personally Identifiable Information for online targeted password guessing.Due to its remarkable guessing performance,the model has drawn considerable attention in password security research.However,through an analysis of the vulnerable behavior of users when constructing passwords by combining popular passwords with their Personally Identifiable Information,we identified that the model fails to consider popular passwords and frequent substrings,and it uses overly broad personal information categories,with extensive duplicate statistics.To address these issues,we propose an improved password guessing model,TGI-FPR,which incorporates three semantic methods:(1)identification of popular passwords by generating top 300 lists from similar websites,(2)use of frequent substrings as new grammatical labels to capture finer-grained password structures,and(3)further subdivision of the six major categories of personal information.To evaluate the performance of the proposed model,we conducted experiments on six large-scale real-world password leak datasets and compared its accuracy within the first 100 guesses to that of TarGuess-I.The results indicate a 2.65%improvement in guessing accuracy.展开更多
In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and d...In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and discourses.Building an independent human rights knowledge system has become a core academic focus in China’s human rights research field.Upholding fundamental principles and breaking new ground are the key methodological principles for the process.China’s human rights research should be rooted in the“cultural lineage”by preserving the essence of fine traditional Chinese culture,guided by the“moral lineage”by adhering to the Marxist view on human rights,and anchored in the“Four-sphere Confidence”by upholding a distinct human rights development path,so as to define the historical coordinates and value stance of China’s independent human rights knowledge system.Meanwhile,it should maintain a high degree of openness in knowledge,theory,and methodology to address emerging rights demands and contribute to building a new global human rights governance order,so as to underscore the mission of China’s independent human rights knowledge system in the contemporary era and China’s responsibility as a major global actor.China’s human rights research should uphold the dialectical unity between the fundamental principles and innovations,and advance the systemic and theoretical interpretation of its independent human rights knowledge.展开更多
In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the d...In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.展开更多
Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke...Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke syndromes,necessitates expeditious and aggressive modification of risk factors.展开更多
Purpose:To describe the characteristics of research outputs using persistent identifiers generated by ResearchGate to gain insight into what publications are shared and disseminated through this functionality,revealin...Purpose:To describe the characteristics of research outputs using persistent identifiers generated by ResearchGate to gain insight into what publications are shared and disseminated through this functionality,revealing their academic and non-academic impact.Design/methodology/approach:A total of 1,092,934 RG-DOIs were collected,using the DataCite API,along with bibliographic metadata for the associated registered output(RG-DOI publications).The subsequent analysis evaluated the publication date,document type,and language.These values were crossreferenced against the full text of a random sample of 666 records to verify accuracy.Findings:RG-DOIs have served primarily to identify and make accessible scholarly gray literature,including posters,presentations,conference papers,and theses,with notable emphasis on publications in Spanish and Portuguese.Around 41,000 citations from Web of Science indexed publications to RG publications are evidence of their infrequent but perceptible use in scholarly discourse.The declining number of registrations of RG-DOIs observed may indicate a shift in researcher preferences to alternative platforms for DOI generation.Research limitations:The study uncovered substantial inconsistencies in DataCite metadata,which can be attributed to the automated DOI registration process and internal changes in the available document types on ResearchGate.Practical implications:The study encountered challenges in conducting a quantitative analysis due to inconsistencies in the metadata.These have potential implications for researchers,practitioners,and librarians relying on RG-DOIs to conduct bibliometric or bibliographic analysis.Originality/value:This study is the first comprehensive analysis of RG-DOIs and,as such,provides a unique perspective into academic gray literature.It also sheds light on the quality of ResearchGate data transmitted to DataCite when registering DOIs.展开更多
The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm ...The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm fertilizing capacity.Among these,sperm concentration and motility are the first parameters to be evaluated through an estimation carried out by expert examiners.展开更多
Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of...Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of abstracting the complex structures of MOFs by identifying and classifying the fundamental building units and connection patterns,simplifying the understanding of MOF structures[3].展开更多
Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In respon...Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In response to the demand for technology to identify improper operations in substation work scenarios,this paper proposes a substation safety action recognition technology to avoid the misoperation and enhance the safety management.In general,this paper utilizes a dual-branch transformer network to extract spatial and temporal information from the video dataset of operational behaviors in complex substation environments.Firstly,in order to capture the spatial-temporal correlation of people's behaviors in smart grid substation,we devise a sparse attention module and a segmented linear attention module that are embedded into spatial branch transformer and temporal branch transformer respectively.To avoid the redundancy of spatial and temporal information,we fuse the temporal and spatial features using a tensor decomposition fusion module by a decoupled manner.Experimental results indicate that our proposed method accurately detects improper operational behaviors in substation work scenarios,outperforming other existing methods in terms of detection and recognition accuracy.展开更多
The Chinese government promotes smoking cessation through smoking cessation clinics(SCCs).This study aimed to identify factors associated with relapse and provide evidence to inform interventions that reduce relapse r...The Chinese government promotes smoking cessation through smoking cessation clinics(SCCs).This study aimed to identify factors associated with relapse and provide evidence to inform interventions that reduce relapse risk.Participants were SCC patients aged≥18 years who enrolled between June 2019 and December 2021,completed follow-up assessments at one and three months,and reported abstinence at one month.Short-term relapse was defined as self-reported smoking at the three-month follow-up.Treatments included counseling,first-line cessation medications,and traditional Chinese medicine(TCM).Logistic regression was used to identify factors associated with short-term relapse.Among 10,724 eligible SCC patients,11.6%experienced short-term relapse.Factors positively associated with relapse included the number of previous quit attempts(1–5 attempts:OR=1.422,95%CI:1.254–1.613,>5 attempts:OR=1.382,95%CI:1.057–1.808),high perceived difficulty in quitting(OR=1.297,95%CI:1.061–1.586),and moderate(OR=1.383,95%CI:1.174–1.629)or weak(OR=1.517,95%CI:1.251–1.841)willingness to quit.Factors negatively associated with relapse included having a college degree or higher(OR=0.796;95%CI:0.650–0.973),high confidence in quitting(OR=0.786;95%CI:0.629–0.983),and use of TCM(OR=0.276;95%CI:0.158–0.482).Enhancing self-efficacy in quitting appears crucial for preventing short-term relapse.The use of TCM may reduce relapse risk and warrants further investigation.展开更多
Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimens...Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimensional system of“safety and stability-economic feasibility-low-carbon and environmental protection,”an influencing factor system for the“Energy Trilemma”in the natural gas industry is constructed.展开更多
Background Delays in first case on-time starts(FCOTS)can lead to inefficiencies in the operating room(OR),dissatisfaction among patients with their providers and staff,and increased facility costs.While the literature...Background Delays in first case on-time starts(FCOTS)can lead to inefficiencies in the operating room(OR),dissatisfaction among patients with their providers and staff,and increased facility costs.While the literature has established standards for improving main OR efficiency,further research is needed in labour and delivery(L&D)units.Therefore,we aimed to identify the barriers to ontime case starts in L&D ORs and to develop interventions to reduce OR case delays.Methods This quality improvement study was conducted at a safety-net hospital,where the average FCOTS was 12%before our initiative.Starting in November 2022,a multidisciplinary team was formed,including representatives from quality,obstetrics,anaesthesiology,nursing and scheduling.We developed failure modes and effects analysis,process mapping and interventions using the Institute for Healthcare Improvement Model for Improvement,testing them through rapid Plan-Do-StudyAct cycles.We used Montgomery rules with statistical process control charts to measure statistically significant changes in both outcome and process measures.Results Contributors to the delays at the patient,provider and systems levels were identified.Interventions targeting structure,process,team members and patient engagement were implemented from December 2022 through December 2023.A 41%increase in the average percentage of on-time first cases compared with the baseline(12%)was observed,based on data collected from August 2022 through November 2022 to postintervention(53%),and this improvement was sustained for 4 months.Additionally,a 69%decrease in the average case delay in minutes from baseline(178 min)was noted 6 months after project initiation(55 min).Conclusions Interventions at the patient,provider and systems levels were identified and implemented,effectively increasing OR on-time case starts on L&D.These can be used in other L&D units to improve FCOTS.展开更多
Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model...Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.展开更多
Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD...Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD)conditions due to the synergistic regulation of many photosensitive genes.Using a set of chromosome segment substitution lines(CSSLs)with the indica cultivar Huanghuazhan(HHZ)as the recipient parent and Basmati Surkh 89-15(BAS)as the donor parent,we identified a QTL locus.展开更多
0 INTRODUCTION Initial subduction involves the complex process of oceanic lithosphere first inserting beneath oceanic or continental lithosphere(Chen et al.,2024;Yang et al.,2022;Stern and Gerya,2018).The modern Izu-B...0 INTRODUCTION Initial subduction involves the complex process of oceanic lithosphere first inserting beneath oceanic or continental lithosphere(Chen et al.,2024;Yang et al.,2022;Stern and Gerya,2018).The modern Izu-Bonin-Mariana(IBM)initial subduction system suggests that identifying the earliest ophiolites,arc igneous and metamorphic complexes(e.g.,blueschist,eclogites)can reconstruct ancient initial subduction systems(Yao et al.,2021;Ishizuka et al.,2011).However,knowledge of ancient subduction initiation is often limited due to poor exposures of rocks formed during the earliest stages of subduction(Chen et al.,2024;Cawood et al.,2009).展开更多
AI is revolutionizing the current paradigm of pharmaceutical research,addressing the challenges encountered at all stages of the process.AI driven drug discovery is based on biomedical big data and new algorithms to i...AI is revolutionizing the current paradigm of pharmaceutical research,addressing the challenges encountered at all stages of the process.AI driven drug discovery is based on biomedical big data and new algorithms to identify drug targets,screen and optimize active compounds,analyze drug properties,and facilitate drug production and quality control.展开更多
文摘In this paper, actual personal identifiable information (PII) texts are analyzed to capture different types of PII sensitivities. The sensitivity of PII is one of the most important factors in determining an individual’s perception of privacy. A “gradation” of sensitivity of PII can be used in many applications, such as deciding the security level that controls access to data and developing a measure of trust when self-disclosing PII. This paper experiments with a theoretical analysis of PII sensitivity, defines its scope, and puts forward possible methodologies of gradation. A technique is proposed that can be used to develop a classification scheme of personal information depending on types of PII. Some PII expresses relationships among persons, some specifies aspects and features of a person, and some describes relationships with nonhuman objects. Results suggest that decomposing PII into privacy-based portions helps in factoring out non-PII information and focusing on a proprietor’s related information. The results also produce a visual map of the privacy sphere that can be used in approximating the sensitivity of different territories of privacy-related text. Such a map uncovers aspects of the proprietor, the proprietor’s relationship to social and physical entities, and the relationships he or she has with others.
基金supported by the National Natural Science Foundation of China(Grant Nos.61672101,U1636119.6186603S,61962059)2018 College Students’Innovation and Entrepreneurship Training Program(D2018127)。
文摘It is widely common that mobile applications collect non-critical personally identifiable information(PII)from users'devices to the cloud by application service providers(ASPs)in a positive manner to provide precise and recommending services.Meanwhile,Internet service providers(ISPs)or local network providers also have strong requirements to collect PIIs for finer-grained traffic control and security services.However,it is a challenge to locate PIIs accurately in the massive data of network traffic just like looking a needle in a haystack.In this paper,we address this challenge by presenting an efficient and light-weight approach,namely TPII,which can locate and track PIIs from the HTTP layer rebuilt from raw network traffics.This approach only collects three features from HTTP fields as users'behaviors and then establishes a tree-based decision model to dig PIIs efficiently and accurately.Without any priori knowledge,TPII can identify any types of PIIs from any mobile applications,which has a broad vision of applications.We evaluate the proposed approach on a real dataset collected from a campus network with more than 13k users.The experimental results show that the precision and recall of TPII are 91.72%and 94.51%respectively and a parallel implementation of TPII can achieve 213 million records digging and labelling within one hour,reaching near to support 1Gbps wirespeed inspection in practice.Our approach provides network service providers a practical way to collect PIIs for better services.
基金support by the National Key R&D Program of China(No.2021YFB3100400)the National Natural Science Foundation of China(Grant Nos.62172216,U20A201092)+6 种基金the Jiangsu Provincial Key Research and Development Program(Nos.BE2022068,BE2022068-2)the Key R&D Program of Guangdong Province(No.2020B0101090002)the Natural Science Foundation of Jiangsu Province(No.BK20211180)the Research Fund of Guangxi Key Laboratory of Trusted Software(No.KX202034)the Research Fund of State Key Laboratory of Integrated Services Networks(Xidian University)(No.ISN23-20)the Fund of Prospective Layout of Scientific Research for NUAA(Nanjing University of Aeronautics and Astronautics)JSPS Postdoctoral Fellowships(No.P21073).
文摘Identity-based threshold signature(IDTS)is a forceful primitive to protect identity and data privacy,in which parties can collaboratively sign a given message as a signer without reconstructing a signing key.Nevertheless,most IDTS schemes rely on a trusted key generation center(KGC).Recently,some IDTS schemes can achieve escrow-free security against corrupted KGC,but all of them are vulnerable to denial-of-service attacks in the dishonest majority setting,where cheaters may force the protocol to abort without providing any feedback.In this work,we present a fully decentralized IDTS scheme to resist corrupted KGC and denialof-service attacks.To this end,we design threshold protocols to achieve distributed key generation,private key extraction,and signing generation which can withstand the collusion between KGCs and signers,and then we propose an identification mechanism that can detect the identity of cheaters during key generation,private key extraction and signing generation.Finally,we formally prove that the proposed scheme is threshold unforgeability against chosen message attacks.The experimental results show that the computation time of both key generation and signing generation is<1 s,and private key extraction is about 3 s,which is practical in the distributed environment.
基金This work was supported by National Natural Science Foundation of China(Nos.62172411,62172404,61972094)。
文摘Personally identifiable information(PII)refers to any information that links to an individual.Sharing PII is extremely useful in public affairs yet hard to implement due to the worries about privacy violations.Building a PII retrieval service over multi-cloud,which is a modern strategy to make services stable where multiple servers are deployed,seems to be a promising solution.However,three major technical challenges remain to be solved.The first is the privacy and access control of PII.In fact,each entry in PII can be shared to different users with different access rights.Hence,flexible and fine-grained access control is needed.Second,a reliable user revocation mechanism is required to ensure that users can be revoked efficiently,even if few cloud servers are compromised or collapse,to avoid data leakage.Third,verifying the correctness of received PII and locating a misbehaved server when wrong data are returned is crucial to guarantee user’s privacy,but challenging to realize.In this paper,we propose Rainbow,a secure and practical PII retrieval scheme to solve the above issues.In particular,we design an important cryptographic tool,called Reliable Outsourced Attribute Based Encryption(ROABE)which provides data privacy,flexible and fine-grained access control,reliable immediate user revocation and verification for multiple servers simultaneously,to support Rainbow.Moreover,we present how to build Rainbow with ROABE and several necessary cloud techniques in real world.To evaluate the performance,we deploy Rainbow on multiple mainstream clouds,namely,AWS,GCP and Microsoft Azure,and experiment in browsers on mobile phones and computers.Both theoretical analysis and experimental results indicate that Rainbow is secure and practical.
基金supported by the Joint Funds of National Natural Science Foundation of China(Grant No.U23A20304)the Fund of Laboratory for Advanced Computing and Intelligence Engineering(No.2023-LYJJ-01-033)+1 种基金the Special Funds of Jiangsu Province Science and Technology Plan(Key R&D ProgramIndustryOutlook and Core Technologies)(No.BE2023005-4)the Science Project of Hainan University(KYQD(ZR)-21075).
文摘TarGuess-I is a leading model utilizing Personally Identifiable Information for online targeted password guessing.Due to its remarkable guessing performance,the model has drawn considerable attention in password security research.However,through an analysis of the vulnerable behavior of users when constructing passwords by combining popular passwords with their Personally Identifiable Information,we identified that the model fails to consider popular passwords and frequent substrings,and it uses overly broad personal information categories,with extensive duplicate statistics.To address these issues,we propose an improved password guessing model,TGI-FPR,which incorporates three semantic methods:(1)identification of popular passwords by generating top 300 lists from similar websites,(2)use of frequent substrings as new grammatical labels to capture finer-grained password structures,and(3)further subdivision of the six major categories of personal information.To evaluate the performance of the proposed model,we conducted experiments on six large-scale real-world password leak datasets and compared its accuracy within the first 100 guesses to that of TarGuess-I.The results indicate a 2.65%improvement in guessing accuracy.
基金a phased result funded by the Special Funds for Basic Scientific Research Expenses of Universities under the Central Government(24CXTD01).
文摘In 2024,China’s human rights research has assumed a distinct“autonomy-oriented shift,”with scholars beginning to refine and construct uniquely Chinese and locally identifiable human rights concepts,categories,and discourses.Building an independent human rights knowledge system has become a core academic focus in China’s human rights research field.Upholding fundamental principles and breaking new ground are the key methodological principles for the process.China’s human rights research should be rooted in the“cultural lineage”by preserving the essence of fine traditional Chinese culture,guided by the“moral lineage”by adhering to the Marxist view on human rights,and anchored in the“Four-sphere Confidence”by upholding a distinct human rights development path,so as to define the historical coordinates and value stance of China’s independent human rights knowledge system.Meanwhile,it should maintain a high degree of openness in knowledge,theory,and methodology to address emerging rights demands and contribute to building a new global human rights governance order,so as to underscore the mission of China’s independent human rights knowledge system in the contemporary era and China’s responsibility as a major global actor.China’s human rights research should uphold the dialectical unity between the fundamental principles and innovations,and advance the systemic and theoretical interpretation of its independent human rights knowledge.
文摘In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.
文摘Patients with cheiro-oral syndrome(COS) often present with minor perioral and upper extremity sensory disturbances,which can be easily overlooked in busy emergency departments(EDs).^([1]) COS,a rare spectrum of stroke syndromes,necessitates expeditious and aggressive modification of risk factors.
基金supported by Grant PID2022-142569NA-I00,funded by MCIN/AEI/10.13039/501100011033 and by the European Union through“ERDF A way of making Europe.”。
文摘Purpose:To describe the characteristics of research outputs using persistent identifiers generated by ResearchGate to gain insight into what publications are shared and disseminated through this functionality,revealing their academic and non-academic impact.Design/methodology/approach:A total of 1,092,934 RG-DOIs were collected,using the DataCite API,along with bibliographic metadata for the associated registered output(RG-DOI publications).The subsequent analysis evaluated the publication date,document type,and language.These values were crossreferenced against the full text of a random sample of 666 records to verify accuracy.Findings:RG-DOIs have served primarily to identify and make accessible scholarly gray literature,including posters,presentations,conference papers,and theses,with notable emphasis on publications in Spanish and Portuguese.Around 41,000 citations from Web of Science indexed publications to RG publications are evidence of their infrequent but perceptible use in scholarly discourse.The declining number of registrations of RG-DOIs observed may indicate a shift in researcher preferences to alternative platforms for DOI generation.Research limitations:The study uncovered substantial inconsistencies in DataCite metadata,which can be attributed to the automated DOI registration process and internal changes in the available document types on ResearchGate.Practical implications:The study encountered challenges in conducting a quantitative analysis due to inconsistencies in the metadata.These have potential implications for researchers,practitioners,and librarians relying on RG-DOIs to conduct bibliometric or bibliographic analysis.Originality/value:This study is the first comprehensive analysis of RG-DOIs and,as such,provides a unique perspective into academic gray literature.It also sheds light on the quality of ResearchGate data transmitted to DataCite when registering DOIs.
文摘The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm fertilizing capacity.Among these,sperm concentration and motility are the first parameters to be evaluated through an estimation carried out by expert examiners.
基金supported by the National Natural Science Foundation of China(22101039,22471027,22311530679)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(22021005)the Fundamental Research Funds for the Central Universities(DUT24LK004).
文摘Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of abstracting the complex structures of MOFs by identifying and classifying the fundamental building units and connection patterns,simplifying the understanding of MOF structures[3].
文摘Smart grid substation operations often take place in hazardous environments and pose significant threats to the safety of power personnel.Relying solely on manual supervision can lead to inadequate oversight.In response to the demand for technology to identify improper operations in substation work scenarios,this paper proposes a substation safety action recognition technology to avoid the misoperation and enhance the safety management.In general,this paper utilizes a dual-branch transformer network to extract spatial and temporal information from the video dataset of operational behaviors in complex substation environments.Firstly,in order to capture the spatial-temporal correlation of people's behaviors in smart grid substation,we devise a sparse attention module and a segmented linear attention module that are embedded into spatial branch transformer and temporal branch transformer respectively.To avoid the redundancy of spatial and temporal information,we fuse the temporal and spatial features using a tensor decomposition fusion module by a decoupled manner.Experimental results indicate that our proposed method accurately detects improper operational behaviors in substation work scenarios,outperforming other existing methods in terms of detection and recognition accuracy.
文摘The Chinese government promotes smoking cessation through smoking cessation clinics(SCCs).This study aimed to identify factors associated with relapse and provide evidence to inform interventions that reduce relapse risk.Participants were SCC patients aged≥18 years who enrolled between June 2019 and December 2021,completed follow-up assessments at one and three months,and reported abstinence at one month.Short-term relapse was defined as self-reported smoking at the three-month follow-up.Treatments included counseling,first-line cessation medications,and traditional Chinese medicine(TCM).Logistic regression was used to identify factors associated with short-term relapse.Among 10,724 eligible SCC patients,11.6%experienced short-term relapse.Factors positively associated with relapse included the number of previous quit attempts(1–5 attempts:OR=1.422,95%CI:1.254–1.613,>5 attempts:OR=1.382,95%CI:1.057–1.808),high perceived difficulty in quitting(OR=1.297,95%CI:1.061–1.586),and moderate(OR=1.383,95%CI:1.174–1.629)or weak(OR=1.517,95%CI:1.251–1.841)willingness to quit.Factors negatively associated with relapse included having a college degree or higher(OR=0.796;95%CI:0.650–0.973),high confidence in quitting(OR=0.786;95%CI:0.629–0.983),and use of TCM(OR=0.276;95%CI:0.158–0.482).Enhancing self-efficacy in quitting appears crucial for preventing short-term relapse.The use of TCM may reduce relapse risk and warrants further investigation.
基金Western Project of the National Social Science Fund of China (22XGL019)Major Project of the National Social Science Fund of China (22&ZD105)+1 种基金Special Academic Research Grant at the Key Research Base of Philosophy and Social Sciences in Sichuan Province (SC24E091)Chengdu Philosophy and Social Science Planning Project 2024 (2024BS072)。
文摘Clarifying the system structure of various influencing factors is a crucial prerequisite for identifying the key action point to address the“Energy Trilemma”in China’s natural gas industry.Based on the three-dimensional system of“safety and stability-economic feasibility-low-carbon and environmental protection,”an influencing factor system for the“Energy Trilemma”in the natural gas industry is constructed.
文摘Background Delays in first case on-time starts(FCOTS)can lead to inefficiencies in the operating room(OR),dissatisfaction among patients with their providers and staff,and increased facility costs.While the literature has established standards for improving main OR efficiency,further research is needed in labour and delivery(L&D)units.Therefore,we aimed to identify the barriers to ontime case starts in L&D ORs and to develop interventions to reduce OR case delays.Methods This quality improvement study was conducted at a safety-net hospital,where the average FCOTS was 12%before our initiative.Starting in November 2022,a multidisciplinary team was formed,including representatives from quality,obstetrics,anaesthesiology,nursing and scheduling.We developed failure modes and effects analysis,process mapping and interventions using the Institute for Healthcare Improvement Model for Improvement,testing them through rapid Plan-Do-StudyAct cycles.We used Montgomery rules with statistical process control charts to measure statistically significant changes in both outcome and process measures.Results Contributors to the delays at the patient,provider and systems levels were identified.Interventions targeting structure,process,team members and patient engagement were implemented from December 2022 through December 2023.A 41%increase in the average percentage of on-time first cases compared with the baseline(12%)was observed,based on data collected from August 2022 through November 2022 to postintervention(53%),and this improvement was sustained for 4 months.Additionally,a 69%decrease in the average case delay in minutes from baseline(178 min)was noted 6 months after project initiation(55 min).Conclusions Interventions at the patient,provider and systems levels were identified and implemented,effectively increasing OR on-time case starts on L&D.These can be used in other L&D units to improve FCOTS.
基金supported by the National Natural Science Foundation of China(62473020).
文摘Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation.
基金supported by the Zhejiang Provincial Natural Science Foundation of China(Grant Nos.LZ24C130004 and LQ24C130008)。
文摘Heading date is one of the most important agronomic traits that directly affect rice yield and determines the regional adaptability in specific growing environments.As a short-day plant,rice can grow under long-day(LD)conditions due to the synergistic regulation of many photosensitive genes.Using a set of chromosome segment substitution lines(CSSLs)with the indica cultivar Huanghuazhan(HHZ)as the recipient parent and Basmati Surkh 89-15(BAS)as the donor parent,we identified a QTL locus.
基金supported by the special fund of the State Key Laboratory of Deep Earth and Mineral Exploration(No.KFDM2025203)the Natural Science Foundation of Liaoning Province(No.2025-MS-037)+2 种基金the National Natural Science Foundation of China(No.41972234)support provided by the China Scholarship Council(No.202306080045)the Geological Society Research Grants-Mike Coward Fund.
文摘0 INTRODUCTION Initial subduction involves the complex process of oceanic lithosphere first inserting beneath oceanic or continental lithosphere(Chen et al.,2024;Yang et al.,2022;Stern and Gerya,2018).The modern Izu-Bonin-Mariana(IBM)initial subduction system suggests that identifying the earliest ophiolites,arc igneous and metamorphic complexes(e.g.,blueschist,eclogites)can reconstruct ancient initial subduction systems(Yao et al.,2021;Ishizuka et al.,2011).However,knowledge of ancient subduction initiation is often limited due to poor exposures of rocks formed during the earliest stages of subduction(Chen et al.,2024;Cawood et al.,2009).
文摘AI is revolutionizing the current paradigm of pharmaceutical research,addressing the challenges encountered at all stages of the process.AI driven drug discovery is based on biomedical big data and new algorithms to identify drug targets,screen and optimize active compounds,analyze drug properties,and facilitate drug production and quality control.
